Management Principles for Data Lakes

Overview

There remains an ever-growing volume of data, with varieties of data assets distributed across cloud and on-premises environments and data often distributed across the globe. IT teams are often plagued by having to reconcile fragmented data sources manually, which is prohibitively time-consuming if business users hope to make timely business decisions based on it. As a result, when business users do get access to data, it is often stale or untrustworthy. Lacking a single source of truth, they are often reticent to even use it in the event that the resulting business decision be flawed as a result.

A call for a systematic approach

New classes of business users such as data scientists are requesting data, and new analytics technologies such as machine learning, data lakes, and artificial intelligence will influence data strategies. Organizations without an enterprisewide data management program in place need to adopt a comprehensive, cloud-focused, and repeatable process to data management. Otherwise, they cannot reliably use their data to drive business-critical decisions without risking noncompliance with a growing number of data-focused regulations.

Build a foundation of trusted data

Informatica’s market-leading platform, backed by proven methodology and a strong partner ecosystem, provides a distinct advantage in ensuring the success of big data projects. Informatica is uniquely poised to help drive business value by delivering successful data lakes, on-premises or in the cloud, with a risk-centric focus that automatically classifies sensitive data and proactively detects threats of unauthorized data access or proliferation. Informatica empowers effective collaboration among data analysts, data stewards, and other business users so that big data is quickly converted into high-quality trusted insights.